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David Zhang
Experienced bioinformatician who enjoys learning and applying the best practices for method development. I focus on developing robust, user-friendly tools that harness transcriptomic data to improve the rate of genetic diagnosis.
Education
PhD, Bioinformatics
University College London
London, UK
Present - 2017
- Thesis: Using transcriptomics to improve the genetic diagnosis rate of rare disease patients.
MSc, Neuroscience
University College London
London, UK
2016 - 2015
- Thesis: The role of mitochondrial dysfunction in Xerodoma pigmentosum
- Grade: Merit (68%)
- Awarded post-graduate support scheme bursary (£10,000)
BSc, Biomedical science
University College London
London, UK
2015 - 2012
- Thesis: Investigating the function of CYFIP1 in the development of rat hippocampal neurons.
- Grade: 2:1 (69%)
H.S.
Queen Elizabeth’s School
Barnet, UK
2012 - 2007
- Grades: Maths (A*), Biology (A*), Chemistry (A*), Sociology (A).
Work Experience
Bioinformatician internship (2 months)
Remote, US
2021
- Goal: Set up an aberrant splicing detection pipeline for drug target discovery in C9orf72 ALS patients.
- Used docker to setup a reproducible workflow for running aberrant splicing analyses on an AWS instance.
Software & programming
Bioconductor packages
N/A
N/A
Present - 2020
- dasper: Detection of aberrant splicing events in RNA-sequencing. Author and maintainer.
- megadepth: BigWig and BAM related utilities. An R wrapper for the megadepth software developed by Chris Wilks. Co-author and maintainer.
- ODER: Optimising the definition of Expressed Regions. Submitted to Bioconductor. Co-author and maintainer.
Python packages
N/A
N/A
Present - 2021
- codino converts a codon design to the expected amino acid frequencies, and vice versa. Author and maintainer.
Web scraping
N/A
N/A
2021
- Applied the python packages Beautiful Soup and Selenium to web scrape information on all UK biotechnology companies.